Extending the scope of atomic-scale simulations
is a critically important goal because these types of simulations
are required to fully understand the mechanisms responsible for
the formation of many interesting nanoscale phenomena such as quantum
dots, precipitate ordering, and mechanical fracture. Such features
are currently beyond the reach of standard atomic scale simulations.
In many situations of practical interest, not all the regions in
a simulation are equally important, motivating the use of multiresolution
approaches to reduce the computational requirements.

Our research program in this area has been focused
on the development of MD based simulations in which only a (changing)
fraction of the atoms are actively considered, while atoms that
lie far away from the feature(s) of interest are treated in a computationally
expedient manner. An example of this approach, (which we call Feature
Activated Molecular Dynamics, or FAMD) is given in Figure 1, which
shows the evolution in an FAMD simulation of a spherical cavity
under constant dynamic hydrostatic tension. The large red atoms
surrounding the cavity are considered with standard MD, while the
small blue ones further away are only subjected to occasional static
relaxation. During the initial phases of the simulation, relatively
few atoms need to be considered, and it is only in the final stages
of the simulation, once the void has cavitated, that most of the
atoms in the simulation cell are activated. The resulting computational
savings are substantial and can be larger than a factor of ten over
the entire simulation, depending on the size of the overall simulation
cell.

Figure 1: Evolution of active
atoms around a cavity subjected to hydrostatic tension. Initially
only few atoms are activated and the simulation proceeds much more
rapidly than a standard MD simulation. Towards the end, most of
the atoms are active and standard MD speeds are achieved.

Another example of this approach applied to a very
different system is shown in Figure 2. Here a collection of about
2,000 point defects (self-interstitials) are introduced into a 1,000,000-atom
silicon lattice and allowed to diffuse and agrgegate in time. Once
again, only the regions of the lattice surrounding the defect clusters
is of interest and the FAMD method tracks these regions as the clusters
grow (or shrink) and diffuse within the lattice. Again, the computational
savings relative to standard MD are substantial. This particular
simulation was performed on a parallel computer platform with 8
processors using a parallel version of the FAMD algorithm.

Figure 2: Snapshots of an FAMD simulation of self-interstitial
clustering in crystalline silicon. Total system size is 1,000,000
atoms but only red atoms are actually evolved with MD. Near end
of simulation, only about 10% of the atoms are evolved with MD.